The present invention relates to a novel method of simulating a process, and particularly relates to a novel process simulator that utilizes simplified mathematical correlations to predict the performance of equipment or subsystems in a process unit.
Process units, such as syngas or other processes, are typically designed using complex simulation programs that include physical property models and require considerable technical expertise to use. Production split, or production quantities, are often driven by market demands; thus, process units are typically designed to allow a certain flexibility to produce different products or product splits, or to produce products in varying quantities. Process units are also designed with certain optimum operating efficiencies, such as catalyst efficiency, membrane separation efficiency, heat transfer efficiency, compressor load, or a number of other performance parameters that may vary during actual operation of the process plant, or that vary with the age of catalyst, or condition of equipment. Actual operation of these process units can thus vary considerably from design conditions, and from optimum conditions.
To minimize costs, and/or maximize production, real-time simulation models are often used to evaluate the real-time operating efficiency of a process unit and to help make operating decisions. These real-time simulation models are typically customized software applications that apply complex simulation programs that include extensive physical properties models and complex solvers to determine the ideal responses of the process unit to current operating conditions. The operations personnel may then compare the results of these complex models with the actual operating results to determine when to take certain actions, such as cleaning equipment, replacing spent catalyst, replacing fouled membranes, or simply changing the operating conditions of the process plant.
Complex process simulators often are not feasible for small, and/or remote process units, because using these complex simulators requires considerable technical skill, and/or significant computing power. Complex process simulators can cost hundreds of thousands to millions of dollars to purchase and install for a single process unit. Furthermore, the process computer and process software application programs, including the simulation programs, require significant expense to maintain the programs and computing platforms. Further yet, the complex simulators often require a technical person with considerable process knowledge and technical training to properly utilize and maintain. Because of the burden created by these issues, some process operating units, particularly smaller units, cannot take advantage of these complex process simulations to assist with day-to-day operations.
In light of the foregoing problems associated with using complex physical property based simulation models, a need exists for an improved method of simulating a process that uses simplified process models, is affordable to smaller process units, and can be used day to day by operating personnel. Furthermore, there is a need for a process simulator wherein the simulator can be used on personal computers, or control system computers that are readily available to operating personnel.